Instructions to use Atnafu/mt5-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Atnafu/mt5-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="Atnafu/mt5-base")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Atnafu/mt5-base") model = AutoModelForSeq2SeqLM.from_pretrained("Atnafu/mt5-base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 45a6d490bd7ec5efe7fbf0967a923e84cda9e8d3ad92620bdb34ac84b1763235
- Size of remote file:
- 2.33 GB
- SHA256:
- 196d7d53c65b0f51d28c22b9bb978f2594d96a1a491902ab4318a8bd1bf0b2e9
路
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